code: def test_feature_importances_w_subestimators():
      rf = Mock()
      tree_1 = Mock()
      tree_1.feature_importances_ = np.array(
          [0.12, 0.10, 0.8, 0.06, 0.03]
      )
      tree_2 = Mock()
      tree_2.feature_importances_ = np.array(
          [0.10, 0.10, 0.8, 0.06, 0.01]
      )
      tree_3 = Mock()
      tree_3.feature_importances_ = np.array(
          [0.09, 0.01, 0.9, 0.12, 0.02]
      )
      tree_4 = Mock()
      tree_4.feature_importances_ = np.array(
          [0.12, 0.10, 0.8, 0.06, 0.01]
      )
      rf.estimators_ = [tree_1, tree_2, tree_3, tree_4]
      rf.feature_importances_ = np.array([0.12, 0.10, 0.8, 0.06, 0.03])
      plot.feature_importances(rf)
  
imports: from functools import partial
  import sys
  from unittest.mock import Mock
  import numpy
  from matplotlib.testing.decorators import image_comparison
  from sklearn_evaluation import plot
label_desc: Use image node_id 21 for calling a global function with example usage: test_feature_importances_w_subestimators() without return types